Database Laboratory2013-10-21

TaeHoon Kim

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Database LaboratoryRegular Seminar

2013-10-21TaeHoon Kim

CryptDB: Protecting Confidentiality with Encrypted Query Process-ing

Raluca Ada Popa, Catherine M. S. Redfield Nickolai Zeldovich, and Hari Balakrishman

MIT CSAIL

SOSP '11 Proceedings of the Twenty-Third ACM Symposium on Op-erating Systems Principles

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Contents

1. Introduction

2. Security Overview

3. Queries Over Encrypted Data

4. Multiple Principals

5. Application Case Studies

6. Discussion

7. Implementation

8. Experimental Evaluation

9. Related Work

10. Conclusion

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Introduction

Theft of private information is a significant problem An adversary can exploit software vulnerabilities to gain

unauthorized access to servers Curious or malicious admin at a hosting or application

provider can snoop on private data One approach to reduce the damage is to encrypt sensitive

data

This paper presents CryptDB A system that explores an intermediate design point to pro-

vide confidentiality for applications that use database management systems

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Introduction

CryptDB addresses two threats 1. A curious database DBA who tries to learn private data 2. An adversary that gains complete control of application

and DBMS servers

6

ApplicationDB Server

hackers

SQL

User 1

User 2

User 3

• cloud.berkeley.edu/data/cryptdb.pptx

Confidential Data Leaks

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Introduction

CryptDB addresses these challenges using three key ideas The first is to execute SQL queries over encrypted data

This idea using a SQL-aware encryption strategy

The second technique is adjustable query-based encryption

The third idea is to chain encryption keys to user passwords, so that each data item in the database can be decrypted only through a chain of keys rooted in the password of one of the users with access to that data

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Security Overview

Threat1 : DBMS Server Compromise

Our approach is to allow the DBMS server to perform query processing on encrypted data as it would on an un-encrypted database

Threat2 : Arbitrary Threats

The solution is to encrypt different data items (e.g., data belonging to different users) with different keys

CryptDB provides strong guarantees in the face of arbitrary server-side compromises

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col1/rank

col2/name

table1 (emp)

SELECT * FROM emp WHERE salary = 100

SELECT * FROM table1 WHERE col3 = x5a8c34

Proxy

60100800100

col3/salary

Application

Security Overview(Threat1)

x4be219

x95c623x2ea887

x2ea887

x934bc1x5a8c34x84cec1x17cea7x5a8c34

?x5a8c34x5a8c34

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Queries Over Encrypted Data

SQL-aware Encryption Random(RND) : in indistinguishability under(IND-CPA)

Deterministic(DET) Allows the server to perform equality check, which means it

can perform selects with equality predicates, equality joins, GROUP BY, COUNT, DISTINCT

Order-preserving encryption(OPE) OPE allows order relations between data items to be estab-

lished based on their encrypted values, without revealing the data itself

If x<y, then OPEk(X) < OPEk(Y), for any secret key K

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Queries Over Encrypted Data

Homomorphic encryption (HOM) HOMk(x)*HOMk(y) = HOMk(x+y)

Join (Join and OPE-JOIN) Join support all operations by DET, OPE-JOIN support joins by order relations

Word Search (SEARCH) Search is used to perform searches on encrypted text to sup-

port operations such as MySQL’s LIKE operator Only support full-word keyword searches

– Cannot support arbitrary regular expressions

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Queries Over Encrypted Data

Adjustable Query-based Encryption Our goal is to use the most secure encryption schemes that

enable running the requested queries

Our idea is to encrypt each data item in one or more onions Each value is dressed in layers of increasingly stronger encryp-

tion To perform optimize adjustable query-based encryption

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Queries Over Encrypted Data

Executing Over Encrypted Data The proxy transforms the query to operate on these onions

For instance, for the schema shown in Figure 3, a reference to the Name column for an equality comparison will be replaced with a reference to the C2-Eq column

Read Query Execution

Write Query Execution The proxy encrypts each inserted column’s value with each onion

layer that has not yet been stripped off in that column

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2

3

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Queries Over Encrypted Data

Improving Security and Performance Minimum onion layers

Application developers can specify the lowest onion encryption In-proxy processing

Since the proxy receives the entire result set from the server, sort-ing these result in the proxy does not require significant amount of computation, and does not increase the bandwidth requirements

Training mode

Onion re-encryption When application performs infrequent queries requiring a low onion

layer, CryptDB could be extended to re-encrypt onions

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Queries Over Encrypted Data

Performance Optimization Developer annotation

If many column are not sensitive, the developer can instead pro-vide explicit annotation indicating the sensitive field

Known query set Use training mode Optimize onion sets

Ciphertext pre-computing and caching To reduce this cost, the proxy pre-computes and caches(for OPES)

encryptions of frequently used constants under different keys

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Multiple Principle: Policy Anno-tations Policy Annotations

1. The developer must define the principal types(using PRINC-TYPE) used in her application, such as users, groups, or mes-sages

2. The developer must specify which columns in her SQL schema contain sensitive data, along with the principals that should have access to data using the ENC_FOR annotation

3. Programmers can specify rules for how to delegate the privi-leges of one principal to other principals, using the speak for relation

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Observation : Each row in certain tables natu-rally

specifies 1. how data should be encrypted

msgid senderid

privmsgs_to:

5 196

recipien-tid

62

msgid msgtext

5 “secret mes-sage”

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privmsgs:

“hello world”

Multiple Principle: Policy Anno-tations

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1. Principals

CREATE TABLE privmsgs ( msgid int, subject varchar(255)msgtext text);CREATE TABLE privmsgs_to ( msgid int, rcpt id int, sender id int,

);CREATE TABLE users ( userid int,username varchar(255),

);

Securing phpBB private messages:

3. HAS_ACCESS_TO2. ENCRYPT_FOR

ENCRYPT_FOR PRINC msgid TYPE msg, ENCRYPT_FOR PRINC msgid TYPE msg

PRINC TYPES physical_user EXTERNAL; PRINC TYPES user, msg;

PRINC sender_id TYPE user HAS_ACCESS_TO PRINC msgid TYPE msg, PRINC rcpt_id TYPE user HAS_ACCESS_TO PRINC msgid TYPE msg

PRINC username TYPE physical_user HAS_ACCESS_TO PRINC userid TYPE user

Multiple Principle: Policy Anno-tations

• cloud.berkeley.edu/data/cryptdb.pptx 18

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Multiple Principle: Key chain-ing

• cloud.berkeley.edu/data/cryptdb.pptx 19

Username: AlicePassword: asdf

Username: TomasPassword: dfga

userid 1

userid 2

msgid 5

SKu1

SKu2

SKm5

SKm5

SKa = dblab

SKb = dblab

ESKa[SKu1]

ESKb[SKu2]

ESKu1[SKm5]

ESKu2[SKm5]

“secret mes-sage”

All key chaining opera-tions done at proxy, keys stored encrypted at DB server

• Also use public key pair

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Application Study

PhpBB e.g)xpressEngine board A widely used open source forum with a rich set of access con-

trol settings

HotCRP A popular conference review application

Grad-apply A graduate admissions system used by MIT EECS

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Discussion / Implementation

CryptDB cannot support on encrypted Data Not support both computation and comparison on the same

column SELECT age*2+10 FROM … WHERE salary > age*2+10

(1)rewritten into a sub-query (2)re-encrypted in the proxy

CryptDB proxy consist of a C++ Lib and a Lua module CryptDB used MySQL proxy CryptDB implementation consists of ~ 18,000 lines of C++

Code and ~150 lines of Lua Code

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Performance Evaluation

Performance environment MySQL 5.1.54 server : 2 machines

2.4 GHz Intel Xeon E5620 4-core processors 12 GB of RAM

CryptDB proxy and the clients : 8 machines 2.4 GHz AMD Opteron 8431 6-core processors 64 GB of RAM

Use a shared Gigabit Ethernet network

Use TPC-C query set

Compare with MySQL CryptDB CryptDB with only Random encryption(RND) :strawman

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Performance Evaluation

Throughput of different types of SQL queries from the TPC-C query

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Related work

Theoretical approaches ([Gentry’10], [Gennaro et al., ’10]) Inefficient

Search on encrypted data (e.g., [Song et al., ’00]) Restricted set of queries, inefficient

Systems proposals (e.g., [Hacigumus et al., ’02])] Lower degree of security, rewrite the DBMS, client-side pro-

cessing

Software checks (e.g., PQL, UrFlow, Resin) No protection against adversaries with complete access to

servers

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Conclusion

We presented CryptDB, a system that provides a practical and a strong level of confidence in the face of two signifi-cant threats

1. A curious database DBA who tries to learn private data 2. An adversary that gains complete control of application

and DBMS servers

Our Evaluation show that CryptDB can support operations over encrypted data

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Note that, All ppt contents is based on “cloud.berkeley.edu/data/

cryptdb.pptx” and paper by Christof Kim(TaeHoon Kim) :D

If ppt contents contains error, plz recommend to me taehun3718@gmail.com :D